A multivariate approach to the identification of surrogate parameters for heavy metals in stormwater
Singh, Anjana, Ayoko, Godwin A., Herngren, Lars F., & Goonetilleke, Ashantha (2013) A multivariate approach to the identification of surrogate parameters for heavy metals in stormwater. Water, Air, & Soil Pollution, 224(1), pp. 1-9.
Stormwater is a potential and readily available alternative source for potable water in urban areas. However, its direct use is severely constrained by the presence of toxic pollutants, such as heavy metals (HMs). The presence of HMs in stormwater is of concern because of their chronic toxicity and persistent nature. In addition to human health impacts, metals can contribute to adverse ecosystem health impact on receiving waters. Therefore, the ability to predict the levels of HMs in stormwater is crucial for monitoring stormwater quality and for the design of effective treatment systems. Unfortunately, the current laboratory methods for determining HM concentrations are resource intensive and time consuming. In this paper, applications of multivariate data analysis techniques are presented to identify potential surrogate parameters which can be used to determine HM concentrations in stormwater. Accordingly, partial least squares was applied to identify a suite of physicochemical parameters which can serve as indicators of HMs. Datasets having varied characteristics, such as land use and particle size distribution of solids, were analyzed to validate the efficacy of the influencing parameters. Iron, manganese, total organic carbon, and inorganic carbon were identified as the predominant parameters that correlate with the HM concentrations. The practical extension of the study outcomes to urban stormwater management is also discussed.
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|Item Type:||Journal Article|
|Keywords:||Partial Least Square (PLS), Surrogate Indicators, Stormwater Quality, Heavy Metals|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > CIVIL ENGINEERING (090500)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > CIVIL ENGINEERING (090500) > Water Quality Engineering (090508)
|Divisions:||Current > Schools > School of Chemistry, Physics & Mechanical Engineering
Current > Schools > School of Earth, Environmental & Biological Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2012 Springer Science+Business Media Dordrecht|
|Copyright Statement:||The final publication is available at link.springer.com|
|Deposited On:||08 Jan 2013 00:35|
|Last Modified:||08 Aug 2014 09:16|
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